* Concordance in molecular genetic analysis of tumour tissue, plasma, and exhaled breath condensate samples from lung cancer patients

Tetik V. , Pelit L., Aldag C., Korba K. , Celebi C., Dizdas T., ...More

JOURNAL OF BREATH RESEARCH, vol.14, no.3, 2020 (Journal Indexed in SCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 3
  • Publication Date: 2020
  • Doi Number: 10.1088/1752-7163/ab739b


Aim. Lung adenocarcinoma is characterized by poor prognosis and short survival rates. Therefore, tools to identify the tumoural molecular structure and guide effective diagnosis and therapy decisions are essential. Surgical biopsies are highly invasive and not conducive for patient follow-up. To better understand disease prognosis, novel non-invasive analytic methods are needed. The aim of the present study is to identify the genetic mutations in formalin-fixed paraffin-embedded (FFPE) tissue, plasma, and exhaled breath condensate (EBC) samples by next-generation sequencing and evaluate their utility in the diagnosis and follow-up of patients with lung adenocarcinoma. Method. FFPE, plasma, and EBC samples were collected from 12 lung adenocarcinoma patients before treatment. DNA was extracted from the specimens using an Invitrogen PureLink Genomic DNA Kit according to the manufacturer's instructions. Amplicon-based sequencing was performed using Ion AmpliSeq Colon and Lung Cancer Research Panel v2. Results. Genetic alterations were detected in all FFPE, plasma, and EBC specimens. The mutations in PIK3CA, MET, PTEN, SMAD4, and FGFR2 genes were highly correlated in six patients. Somatic and novel mutations detected in tissue and EBC samples were highly correlated in one additional patient. The EGFR p.L858R and KRAS p.G12C driver mutations were found in both the FFPE tissue specimens and the corresponding EBC samples of the lung adenocarcinoma patients. Conclusion. The driver mutations were detected in EBC samples from lung adenocarcinoma patients. The analysis of EBC samples represents a promising non-invasive method to detect mutations in lung cancer and guide diagnosis and follow-up.